PartCycle Technologies announces “Inventory A.I.”, an industry-first innovation developed to clearly communicate part descriptions and provide accurate quality ratings on used auto parts sold through the PartCycle Marketplace.

Most used parts sourcing solutions available today only display raw notes made when an automotive recycler enters a part into their inventory management system using industry codes, subjective ratings, and shorthand. These raw notes are typically impossible to read for those who are untrained or unfamiliar with automotive recycling.

The raw notes may include important, and otherwise unavailable, details such as paint color, quality or may indicate the existence, location and extent of any damage on the part. Without this information it can be a challenge for a buyer to know what they are purchasing without calling the seller directly.

When browsing inventory on PartCycle, all of the information a prospective buyer needs to know about condition and quality will be displayed right next to the inventory in an easy to read format, eliminating the need for a phone call.

Inventory A.I. uses a two-step process to create and display more information about the inventory.

Step 1:

PartCycle uses a sophisticated translation engine to automatically recognize and convert the shorthand, industry codes and other raw data in sellers’ inventory notes, into easily-understood, actionable, information for the buyer.

Step 2:

Assign a commonly understood condition rating or classification.

After translating inventory data, the Inventory A.I. system then evaluates each parts’ final description, mileage, and any identified damage to assign a clear, easy to understand, Amazon.com-style, condition rating to each part. On PartCycle, these part ratings include “Like New,” “Very Good,” “Good” or “Fair.”

Inventory A.I. also prevents the listing of parts which may fall short of the expectations a modern buyer has when shopping online. With the new A.I.’s part description and familiar grading system, PartCycle can provide a better overall shopping experience and reduce the amount of issues and returns from incorrectly-purchased parts.